Plastic film production defect detection method and system based on image processing

A defect detection and image processing technology, applied in image data processing, image analysis, image enhancement, etc., can solve the problems of heavy workload, impact of brightness changes, high missed detection rate, etc., to achieve accurate acquisition and reduce gray level change errors Effect

Active Publication Date: 2022-05-13
江苏豪尚新材料科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, the existing problems in the prior art are: manual detection of plastic film defects has a large workload and a high rate of missed detection
Using image recognition to detect brightness changes, since it is a plastic film defect detection, the defect detection through the light source will inevitably cause reflections, which will affect the brightness change, and the defect detection may be affected

Method used

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  • Plastic film production defect detection method and system based on image processing
  • Plastic film production defect detection method and system based on image processing
  • Plastic film production defect detection method and system based on image processing

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Embodiment 1

[0050] An embodiment of the present invention provides a method for detecting defects in plastic film production based on image processing, such as figure 1 shown, including:

[0051] S101. Acquire the surface image of the plastic film and its grayscale image.

[0052] Among them, the grayscale image is also called the grayscale image. The logarithmic relationship between white and black is divided into several levels, called gray scale. The gray scale is divided into 256 levels.

[0053] S102. Divide the grayscale image into regions to obtain all feature extraction spaces.

[0054] Among them, the feature extraction space is equivalent to dividing the entire grayscale image into blocks.

[0055] S103. Perform Gaussian kernel convolution on each feature extraction space to obtain the gray value of each Gaussian kernel template.

[0056] Among them, the convolution operation is to slide the convolution kernel from left to right and from top to bottom in the form of a windo...

Embodiment 2

[0073] The main purpose of this embodiment is to detect production defects in the plastic film production process through the plastic film image and the set light source.

[0074] An embodiment of the present invention provides a method for detecting defects in plastic film production based on image processing, such as figure 2 shown, including:

[0075] S201. Add an external light source to acquire a surface image of the plastic film.

[0076] By installing an image acquisition device at the entrance of the coiler, the image acquisition device includes: a common RGB camera and a planar light source. The surface of the plastic film is illuminated by a planar light source, and the surface image of the plastic film is collected by the camera. The positions of the planar light source and the camera are fixed, and there is no effect of scattering on the light source. The detection object is a white transparent plastic film, and the main defects are: gel defects.

[0077] S202...

Embodiment 3

[0106] Embodiments of the present invention provide a plastic film production defect detection system based on image processing, such as image 3 As shown, including acquisition unit, processing unit, calculation unit and control unit:

[0107] The acquisition unit sets the camera directly above the entrance of the coiler to collect the surface image of the plastic film on the production line;

[0108] The processing unit inputs the image collected by the acquisition unit into the data master, and uses the data master to preprocess the image to obtain a grayscale image of the surface of the plastic film; perform feature extraction on the grayscale image to obtain the grayscale of the plastic film The change descriptor, according to the gray scale change descriptor, evaluates the defects of the plastic film, and obtains the rough positioning abnormal area;

[0109] The calculation unit uses the data master to process the abnormal area obtained by the processing unit with an en...

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Abstract

The invention relates to the field of defect detection, in particular to a plastic film production defect detection method based on image processing, which comprises the following steps: acquiring a plastic film grey-scale map; performing Gaussian kernel convolution on each feature extraction space in the grey-scale map to obtain each Gaussian kernel template grey-scale value; constructing a histogram in a gradient direction, and adjusting a standard deviation parameter of a Gaussian convolution function according to the histogram to obtain an adjusted gray value of each Gaussian kernel template; obtaining a gray scale change descriptor of each Gaussian kernel template according to each adjusted gray scale value, and further obtaining a gray scale change descriptor of the feature extraction space; obtaining an abnormal region in the feature extraction space according to the gray scale change descriptor of the feature extraction space; determining all defect areas according to gray level change conditions of the abnormal areas and the normal areas before and after light source enhancement; and carrying out edge detection on the defect area to obtain a defect position. The method is used for carrying out defect detection on the plastic film, and the defect detection efficiency can be improved through the method.

Description

technical field [0001] This application relates to the field of defect detection, in particular to a method and system for detecting defects in plastic film production based on image processing. Background technique [0002] Plastic film is widely used in life because of its good performance. However, in the production process of the plastic film, due to improper operation or process problems, there will be various defects on the surface of the plastic film after production, which will affect the use of the plastic film. Therefore, it is necessary to carry out defect detection on the plastic film after production. [0003] In the prior art, the plastic film defect detection is mainly through manual detection, and there is also a plastic film detection through image recognition technology combined with different light beams, and the defect detection is realized by using brightness changes. [0004] However, there are problems in the prior art that the workload of manual det...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06T7/11G06T7/13G06T7/90G06T5/40G06T5/20G06T5/00
CPCG06T7/0002G06T5/40G06T7/11G06T7/13G06T5/007G06T5/20G06T5/002G06T7/90G06T2207/20032G06T2207/30168Y02P90/30
Inventor 黄高峰
Owner 江苏豪尚新材料科技有限公司
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